train: change lr
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@ -8,7 +8,7 @@ finetuning_type: lora
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lora_target: q_proj,v_proj
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### dataset
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dataset: alpaca_en
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dataset: alpaca_gpt4_zh
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template: llama2
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cutoff_len: 1024
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max_samples: 100000
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@ -16,7 +16,7 @@ overwrite_cache: true
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preprocessing_num_workers: 16
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### output
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output_dir: ./saves/LLaMA2-7B/lora/train_24_8_12_23_21
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output_dir: ./saves/LLaMA2-7B/lora/train_24_8_13_07_26
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logging_steps: 3
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save_steps: 100
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plot_loss: true
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@ -25,7 +25,7 @@ overwrite_output_dir: true
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### train
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per_device_train_batch_size: 2
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gradient_accumulation_steps: 8
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learning_rate: 5.0e-5
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learning_rate: 1.5e-4
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num_train_epochs: 10
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lr_scheduler_type: cosine
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warmup_ratio: 0.1
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